1. Introduction

Cyber-physical systems (CPSs) are generally defined as integration of computing and communications technology in order to take control of physical elements [1]. Smart Grid, as an example of a CPS, is a modern power infrastructure to enhance efficiency, reliability, and security [2] along with stable renewable energy production and alternative energy resources. Smart Grid has been designed and implemented through modern communication technologies and automatic control systems [3–5]. Establishing such a complex and elaborate system needs the contribution of sundry technologies. Moreover, everyday life and power networks are inextricably intertwined nowadays. In that every failure, even small, imposes skyrocketing economic and human costs. Therefore, designing a stable and reliable system appears inevitable.

Recently, wireless sensor and actuator network (WSAN) applications have entered a new era of CPS developments like cyber transport system (CTS) and specifically Smart Grid as our research focus [6]. There are various factors which conspicuously impact upon the performance of Smart Grid. Among all the factors, online monitoring and reacting have great capabilities in improving reliability which can be provided by WSANs in every part of Smart Grid assemblage, from generation to consumption [7, 8].

In order to describe the performance of WSANs, several analytical models are introduced in the literature. Some of these models are complicated enough not to be able to be implemented. On the other hand, some others suffer from their low precision due to simplifying and ignoring some parameters such as retransmission

A Reliable Communication Model Based on IEEE802.15.4 for WSANs in Smart Grids

DOI: http://dx.doi.org/10.5772/intechopen.84288

Most significantly, a vast majority of the models reach a consensus on using Poisson traffic pattern as the distribution of network input traffic [13–17]. However, delving further into the issue reveals that applications like remote monitoring and Smart Grid generate data with deterministic distribution. In other words, in these applications, each node produces data in a periodic pattern. To illustrate the concept, consider an AMI connected in a consumer side for monitoring and controlling. Based on AMI type and its protocol, the node sends data to the control center every second or minute which this fact shows that AMI data generation is

The main contribution of this paper is designing a novel analytical model for IEEE802.15.4 standard. The proposed model is specifically appropriate for applications in which the data is periodically generated such as in industry applications and Smart Grid. In these applications, on the one hand, packets are being produced based on a certain periodic time pattern. On the other hand, service time is always a random variable with general distribution. Therefore, service time might temporarily exceed the period time which, as an inevitable consequence, some packets might encounter a busy channel and be dropped. We solve this problem by proposing our MAC-level queue. We demonstrate that the proposed MAC-level queue not only increases the throughput, but also the direct connection between the generation (sensors) and communication packet systems is eliminated which makes the

Moreover, in order to enhance the proposed model, we have employed retransmission scheme, variable packet length, and saturated traffic condition.

As stated by the Electric Power Research Institute (EPRI), one of the most challenges facing Smart Grid deployment is related to cyber security, and due to the increasing potential of cyberattacks and incidents against this critical sector, it becomes more and more interconnected. A large part of research of many organizations working on the development of Smart Grid such as NIST, NERC-CIP, ISA, IEEE 1402, and NIPP are devoted to security programs. In this paper we suggested a well-known standard, IEEE802.15.4, which the wireless link will be secured in different layers. For example, regarding secure communications, the MAC sublayer offers facilities which can be harnessed by upper layers to achieve the desired level of security. Higher-layer processes may specify keys to perform symmetric cryptography to protect the payload and restrict it to nodes or just a point-to-point link; these nodes can be specified in access control lists. Furthermore, MAC computes freshness checks between successive receptions to ensure that presumably old frames, or data which is no longer considered valid, do not transcend to higher layers. In addition, there is another insecure MAC mode, which allows access control lists merely as a means to decide on the acceptance of frames according to

The rest of the paper is organized as follows. In Section 2, we summarize related work. Section 3 lists the main contributions of the paper and their relation with literature. In this section we proposed an extended Markov.

Reliability is analyzed accurately in Section 4. In addition, an accurate analysis of packet service time and end-to-end delay is investigated in Section 5. Numerical

and buffer.

periodic [18–23].

system far more stable.

their (presumed) source.

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1.1 Cybersecurity

Due to WSANs' low costs, they can specifically affect the distributed generation and the production of renewable energy in generation part. Moreover, posts, overhead, and underground transmission lines are better to be online monitored through WSANs in transmission and distribution part. Eventually, WSANs can be employed in consumption part for substation and residential distribution networks, especially smart meters (AMI) [9] which are shown in Figure 1. Although WSANs provide numerous advantages, they encounter some challenges in issues such as real-time data delivery and high-rate data generation, since they have not been specifically designed for Smart Grid.

As often as not, WSAN applications utilize IEEE802.15.4 which take advantage of a low-power link leading to a low data rate transmission (250 kb/s) [10].

Impulsive and robust noises of a power system environment and IEEE802.15.4 standard's intrinsic challenges force us to provide a minimum quality of service (QoS) level to control and monitor applications of Smart Grid [11].

The delay and reliability of WSAN are two prominent parameters in Smart Grid. In order to reach a required QoS level through optimizing network parameters, an elaborate analytical model is essential which is substantially similar to the reality. Table 1 depicts a summary of the most important applications in Smart Grid and their QoS levels in terms of data rate, latency, and reliability [2, 12]. As the table shows, in contrast to the reliabilities, the range of delays are relatively high.

Figure 1.

Smart grid ecosystem monitoring and controlling via WSAN.


#### Table 1.

Communication requirements of smart grid technologies.
